I am working with 2D images and I aim to perform a Karhunen-Loeve decomposition to reduce the dimension of my data. As my images do not have the same dimensions and meshes, I have performed interpolation on them to have a common mesh and flatten them to have 1D fields ready to be used with the SVD KL algorithm ( KarhunenLoeveSVDAlgorithm - OpenTURNS 1.19 documentation)
But the common mesh I use is quite thin, so the size of my dataset becomes large very quickly with the computation time that goes with it. I was recommended to use the ‘KarhunenLoeveSVDAlgorithm-UseRandomSVD’ flag to trigger the stochastic SVD algorithm use at the OT users’ days, but it does not seem to speed up the algorithm… Indeed, nothing really change when I look at computation times for the few tries i have done, it seems that the algorithm isn’t really triggered.
Is there something else I need to do to speed up the algorithm ?
Thaks in advance !